Metric details with threshold from accuracy metric
score
threshold
logloss
0.284821
nan
auc
0.903691
nan
f1
0.653333
0.694369
accuracy
0.870647
0.694369
precision
0.935764
0.694369
recall
0.501862
0.694369
mcc
0.625307
0.694369
Confusion matrix (at threshold=0.694369)
Predicted as Medical
Predicted as Surgical
Labeled as Medical
3311
37
Labeled as Surgical
535
539
Learning curves
Decision Tree
Tree #1
Rules
if (Type of Admission > 0.5) and (Total Costs <= 11941.71) and (CCS Procedure Description > 24.5) then class: Medical (proba: 95.81%) | based on 6,707 samples
if (Type of Admission > 0.5) and (Total Costs > 11941.71) and (CCS Procedure Code <= 176.5) then class: Medical (proba: 53.93%) | based on 2,253 samples
if (Type of Admission <= 0.5) and (APR DRG Code <= 552.5) and (CCS Procedure Code > 0.5) then class: Surgical (proba: 92.8%) | based on 1,681 samples
if (Type of Admission > 0.5) and (Total Costs > 11941.71) and (CCS Procedure Code > 176.5) then class: Medical (proba: 96.57%) | based on 1,137 samples
if (Type of Admission <= 0.5) and (APR DRG Code > 552.5) and (APR DRG Code <= 906.5) then class: Medical (proba: 97.23%) | based on 723 samples
if (Type of Admission > 0.5) and (Total Costs <= 11941.71) and (CCS Procedure Description <= 24.5) then class: Medical (proba: 60.03%) | based on 673 samples
if (Type of Admission <= 0.5) and (APR DRG Code <= 552.5) and (CCS Procedure Code <= 0.5) then class: Medical (proba: 100.0%) | based on 75 samples
if (Type of Admission <= 0.5) and (APR DRG Code > 552.5) and (APR DRG Code > 906.5) then class: Surgical (proba: 100.0%) | based on 14 samples